Network based search services, Internet search engines, voice search, local search, and various other technologies for searching and retrieving information have become increasingly important for helping people find information. Voice search involves a coupling of voice recognition and information retrieval. An uttered phrase is automatically recognized as text, and the text is submitted as a query to a search service. For example, a person may use a mobile phone equipped with a voice search application to find a restaurant by speaking the name of the restaurant into the mobile device, and the mobile device may recognize the spoken restaurant name (i.e., convert it to text) and transmit the text of the restaurant name to a remote search service such as a business directory. Local search is a special case of search where listings of business establishments, firms, organizations, or other entities have been used to enable mobile devices to search same. Consider the following example.
A user may be interested in finding information about a business listed in a directory as “Kung Ho Cuisine of China”. However, the user formulates a query as “Kung Ho Restaurant”. Currently, a search for this listing will not take advantage of statistical parallels between parts of the query and listing forms. Furthermore, erroneous listings, e.g. “Kung Ho Grocery” may be returned as a relevant match.
Discussed below are techniques related to statistical intra-language machine translation, and applications thereof to speech recognition, search, and other technologies.